CN111524081A - Lung image angle correction method and device, electronic equipment and storage medium - Google Patents
Lung image angle correction method and device, electronic equipment and storage medium Download PDFInfo
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- 210000004072 lung Anatomy 0.000 title claims abstract description 346
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- G06T7/60—Analysis of geometric attributes
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract
The embodiment of the invention provides a lung image angle correction method, a lung image angle correction device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a lung region in the lung image; extracting an initial outer contour of the lung region; determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one; and determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle. The lung image angle correction method, the device, the electronic equipment and the storage medium provided by the embodiment of the invention realize automatic angle correction of the lung image, and simultaneously, false alarm boundary points are screened out from the fine outer contour, so that the accuracy of the lung contour is improved, and the accuracy of the angle correction is improved.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and an apparatus for correcting an angle of a lung image, an electronic device, and a storage medium.
Background
With the continuous improvement of medical level, the lung images shot aiming at lung pathological changes become a powerful helper for diagnosing various lung diseases. Under the influence of factors such as the shooting environment and the standing posture of the patient, the lung images of the patient have a certain inclination angle, and the inclination angles of the lung images of different patients have larger difference. In this case, the doctor needs to repeatedly adjust the angle for reading the lung image to adapt to the lung images at various inclination angles, which limits the speed and quality of diagnosis performed by the doctor, and also easily causes diagnostic errors such as missed diagnosis and false detection.
Therefore, it is an urgent need to solve the problem of providing a method and apparatus for correcting an angle of a lung image, which can accurately correct the lung image to a more standard angle.
Disclosure of Invention
The embodiment of the invention provides a lung image angle correction method, a lung image angle correction device, electronic equipment and a storage medium, which are used for solving the problems that the existing lung image has an inclination angle and the difference of the inclination angles of the lung images of different patients is large.
In a first aspect, an embodiment of the present invention provides a method for correcting an angle of a lung image, including:
determining a lung region in the lung image;
extracting an initial outer contour of the lung region;
determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one;
and determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
Optionally, the determining the fine outer contour of any one of the left side and the right side of the initial outer contour based on the distance between each boundary point of the any one of the left side and the right side of the initial outer contour specifically includes:
dividing the initial outer contour into a left side and a right side;
clustering the boundary points on any side based on the distance between the boundary points on any side to obtain a plurality of point sets for any side;
determining a fine outline of the any side based on a point set of the any side with the maximum number of boundary points.
Optionally, the dividing the initial outer contour into left and right sides specifically includes:
and taking the boundary point with the minimum abscissa in the current row of the initial outer contour as a left boundary point, taking the boundary point with the maximum abscissa as a right boundary point, and updating the next row into the current row.
Optionally, the clustering, based on the distance between the boundary points on any side, the boundary points on any side to obtain a plurality of point sets for any side specifically includes:
if the minimum distance between the current boundary point on any side and each boundary point in each point set on any side is smaller than a preset distance threshold, adding the current boundary point into the point set corresponding to the minimum distance, and updating the next boundary point on any side as the current boundary point; otherwise, a new point set for any side is created, the current boundary point is added into the new point set, and the next boundary point on any side is updated to be the current boundary point.
Optionally, the determining a tilt angle of the lung region based on the fine outer contours of the left and right sides, and performing angle correction on the lung image based on the tilt angle specifically includes:
carrying out ellipse fitting on the fine outer contours of the left side and the right side to determine the inclination angle of the lung region;
and performing angle correction on the lung image based on the inclination angle.
Optionally, the ellipse fitting is performed on the fine outer contours of the left and right sides to determine the inclination angle of the lung region, and then the method further includes:
and if the inclination angle of the lung region is larger than a preset angle threshold, correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left lung region and the right lung region of the lung region.
Optionally, the correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left and right lung regions of the lung region specifically includes:
determining a first included angle between a connecting line of a top point and a bottom point of a left lung area of the lung area and the vertical direction, a second included angle between a connecting line of a top point and a bottom point of a right lung area and the vertical direction, and a third included angle between a connecting line of a top point of the left lung area and a top point of the right lung area and the horizontal direction;
and correcting the inclination angle of the lung region based on the first included angle, the second included angle and the third included angle.
In a second aspect, an embodiment of the present invention provides an apparatus for correcting an angle of a lung image, including:
a lung region determining unit for determining a lung region in the lung image;
an initial outline extraction unit for extracting an initial outline of the lung region;
a fine outer contour determining unit for determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one;
and the angle correction unit is used for determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
In a third aspect, an embodiment of the present invention provides an electronic device, including a processor, a communication interface, a memory, and a bus, where the processor and the communication interface, the memory complete mutual communication through the bus, and the processor may call a logic command in the memory to perform the steps of the method provided in the first aspect.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method as provided in the first aspect.
According to the lung image angle correction method, the device, the electronic equipment and the storage medium provided by the embodiment of the invention, the fine outer contours of the left side and the right side are determined based on the distance between each boundary point on any one of the left side and the right side of the initial outer contour of the lung region, then the inclination angle of the lung region is determined based on the fine outer contours of the left side and the right side, and the angle correction is carried out according to the inclination angle, so that the automatic angle correction of the lung image is realized, meanwhile, false alarm boundary points are screened out from the fine outer contours, the accuracy of the lung contour is improved, and the accuracy of the angle correction is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a lung image angle correction method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for extracting a fine outline according to an embodiment of the present invention;
fig. 3 is a schematic flow chart illustrating a tilt angle correction method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a first included angle, a second included angle, and a third included angle provided in an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for correcting an angle of a lung image according to another embodiment of the present invention;
fig. 6 is a schematic diagram illustrating an effect of the angle correction method according to the embodiment of the present invention;
FIG. 7 is a schematic structural diagram of an apparatus for angle correction of lung images according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
With the continuous improvement of medical level, the lung images shot aiming at lung lesions become necessary basis for diagnosing various lung diseases. The lung images are not stable in shooting quality due to the influence of factors such as shooting environments and standing postures of patients, the lung images of the patients have certain inclination angles, and the inclination angles of the lung images of different patients are different greatly. However, in the existing lung diagnosis work, the lung images are not preprocessed, and doctors need to repeatedly adjust the reading angle to adapt to the lung images at various inclination angles, so that the reading difficulty of the doctors is increased, and the diagnosis speed and quality of the doctors are limited.
Accordingly, an embodiment of the present invention provides a method for correcting an angle of a lung image. Fig. 1 is a schematic flowchart of a method for correcting an angle of a lung image according to an embodiment of the present invention, as shown in fig. 1, the method includes:
in step 110, the lung region in the lung image is determined.
Specifically, the lung image is a lung image that needs to be corrected by oblique angle, and the lung image may be a DR (Digital Radiography) image or a CT (Computed Tomography) image, which is not limited in this embodiment of the present invention. After acquiring the lung image to be corrected, determining the lung area in the image. Here, the segmentation method based on deep learning, for example, the neural network model may be used to determine the lung region in the lung image, the conventional segmentation method may be used to determine the lung region in the lung image, for example, the segmentation method based on the threshold, the segmentation method based on the region growing, or the segmentation method based on the genetic algorithm, and the segmentation of the lung region may be performed by combining the deep learning and the conventional segmentation method, which is not specifically limited in the embodiment of the present invention.
Optionally, the lung image is input into a deep neural network model, and the deep neural network model analyzes and calculates the probability of each pixel point in the input lung image in the candidate lung region based on the topological structure of the candidate lung region, and determines and outputs the lung region of the lung image. The deep neural network model may be trained based on the lung image of the sample and the lung region in the lung image of the sample. Additionally, the deep neural network model may be a fully convolutional neural network.
After the lung region of the lung image output by the deep neural network model is obtained, the lung region output by the deep neural network can be optimized by combining a traditional segmentation method, and noise in the lung region is further removed. For example, the lung region may be analyzed for connected components, wherein the connected components with smaller areas are filtered, and the connected components with larger areas are reserved as the optimized lung region.
Specifically, contour extraction is performed on the lung region to obtain an initial outer contour of the lung region. Wherein the initial outer contour of the lung region can describe the general shape of the entire lung region. Here, the initial outer contour of the lung region may be obtained by using a connected component extraction method or an edge detection method, which is not particularly limited in the embodiment of the present invention.
In step 130, a fine outer contour of the side is determined based on the distance between each boundary point of either of the left and right sides of the initial outer contour.
Specifically, the contour extraction method adopted in the last step when contour extraction is performed on the lung region is sensitive to noise, and therefore, there may be a case of segmentation error, resulting in that the extracted initial outer contour includes false alarm boundary points. In addition, the lung region includes left and right lung regions, and a large gap exists between the left and right lung regions, and when the outer contour of the lung region is extracted, the boundary of the gap between the left and right lung regions is also output as the outer contour of the lung region by the contour extraction method, so that the accuracy of the extracted initial outer contour is poor.
In view of the above situation, the embodiment of the present invention extracts boundary points on the left and right sides in the initial outline to eliminate false alarm boundary points caused by the gap between the left and right lung regions. The left side of the initial outer contour is formed by boundary points close to the left in the initial outer contour, and the right side of the initial outer contour is formed by boundary points close to the right in the initial outer contour. Thereupon, the fine outer contour of any side is determined based on the distance between the respective boundary points of that side. Consider that the true contour of the lung region should be continuous, i.e. any boundary point on the true contour is very close in distance to its neighboring boundary points on the true contour, while the false alarm boundary points are relatively far from each boundary point on the true contour. Therefore, the false alarm boundary points can be removed from the boundary points on any side based on the distance between the boundary points on the side, and the fine outline of the side can be obtained.
And 140, determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
Specifically, after obtaining the fine outer contours of the left and right sides, the angle of inclination of the lung region with respect to the horizontal or vertical direction can be determined. Then, based on the inclination angle, the lung image is subjected to angle correction. Optionally, the entire lung image may be rotated based on the angle of inclination to achieve angular rectification; alternatively, the lung image may be rotated based on the inclination angle to achieve the angular correction, considering that the main diagnostic basis of the lung image is the lung region, which is not particularly limited in the embodiment of the present invention.
According to the method provided by the embodiment of the invention, the fine outer contours of the left side and the right side are determined based on the distance between each boundary point on any one of the left side and the right side of the initial outer contour of the lung region, then the inclination angle of the lung region is determined based on the fine outer contours of the left side and the right side, and angle correction is carried out according to the inclination angle, so that automatic angle correction of lung images is realized, meanwhile, false alarm boundary points are screened out from the fine outer contours, the accuracy of the lung contours is improved, and the accuracy of the angle correction is improved.
Based on the foregoing embodiment, fig. 2 is a schematic flow chart of a fine outline extraction method according to an embodiment of the present invention, as shown in fig. 2, in the method, step 130 specifically includes:
Specifically, the boundary point on the left side in the initial outline is taken as a left boundary point, and the boundary point on the right side in the initial outline is taken as a right boundary point, so that the left and right division of the initial outline is realized. And aiming at any side of the initial outer contour, clustering each boundary point of the side based on the distance between each boundary point of the side to obtain a plurality of point sets aiming at the side. Any point on any side is concentrated and comprises a plurality of boundary points which are distributed continuously. Because the boundary points on the real contour of the side are not only continuously distributed, but also the number of the boundary points continuously distributed on the real contour of the side is more than the number of the false alarm boundary points continuously distributed, a point set with the side containing the most boundary points can be screened out, the boundary points in the point set are taken as the boundary points on the fine contour of the side, and the boundary points in the rest point sets are taken as the false alarm boundary points to be removed, so that the fine contour of the side is obtained.
According to the method provided by the embodiment of the invention, each boundary point on any side is clustered based on the distance between the boundary points on the side to obtain a plurality of point sets, and the fine outer contour of the side is determined based on the point set with the largest number of boundary points, so that the accuracy of contour extraction is improved.
Based on any of the above embodiments, in the method, step 131 specifically includes:
and taking the boundary point with the minimum abscissa in the current row of the initial outline as a left boundary point, taking the boundary point with the maximum abscissa as a right boundary point, and updating the next row into the current row.
Specifically, the initial outer contour is traversed transversely, the boundary point with the smallest abscissa in each row is used as a left boundary point, and the boundary point with the largest abscissa in each row is used as a right boundary point, so that the initial outer contour is divided into the left side and the right side.
Optionally, in the lung image after the contour extraction, the pixel value of the pixel point at the initial contour of only the lung region is not 0, and the pixel values of the pixel points in other regions are 0, so that the lung image after the contour extraction can be traversed laterally.
Assuming that the size of the lung image is n × m, the abscissa range of a pixel in the lung image is [0, n ], and the ordinate range of the pixel is [0, m ], if the coordinate of any pixel is (i, j), the pixel value of the pixel is represented as Val (i, j). The specific transverse traversing process may be:
starting from the first row of the lung image, traversing all pixel points of the current row; if Val (i, j)! If the value is 0, recording the value of the abscissa i of the pixel point until all pixel points of the current row are traversed to obtain the pixel point (i) with the minimum abscissaminJ) and the pixel point (i) with the largest abscissamaxJ) and the pixel point (i)minJ) and a pixel point (i)maxJ) as left and right boundary points, respectively; then, the next row is taken as the current row, and the transverse traversal is continued until the last row of the lung image is traversed.
Based on any of the above embodiments, in the method, the step 132 specifically includes:
if the minimum distance between the current boundary point on any side and each boundary point in each point set on the side is smaller than a preset distance threshold, adding the current boundary point into the point set corresponding to the minimum distance, and updating the next boundary point on the side as the current boundary point; otherwise, a new point set for the side is created, the current boundary point is added into the new point set, and the next boundary point of the side is updated to be the current boundary point.
Specifically, considering either side of the lung region, for example, the left side of the left lung region, the true outer contour of the left lung region may be understood as a left edge continuous curve from the lung tip of the left lung to the lung bottom end of the left lung, and the true outer contour of the right lung region may be understood as a right edge continuous curve from the lung tip of the right lung to the lung bottom end of the right lung, and for a single curve, whether the left edge continuous curve or the right edge continuous curve, the single curve is divided into horizontal rows, and each row has only one boundary point. Therefore, when the initial outer contour of the lung region is divided left and right, only the leftmost boundary point and the rightmost boundary point are retained in each row, and the left and right initial outer contours of the lung region correspond to the left and right initial outer contours, respectively. On the basis, the boundary points of the initial outer contour of the left lung area or the right lung area are traversed in a longitudinal traversal mode according to the sequence from top to bottom or from bottom to top to find out the point set with the maximum number of the continuously distributed boundary points in the side as the fine outer contour of the side, so that false alarm boundary points in the initial outer contour of the lung area on any side are filtered out, and the continuity of the outer contour of the lung area on any side is ensured.
Taking any lung area as an example, when traversing the first boundary point in the initial outer contour of the lung area on the side, the point set does not exist on the side, so a point set for the side is created, and the first boundary point is added to the point set. If the minimum distance between the current boundary point and each boundary point in each point set of the side is smaller than a preset distance threshold value, adding the current boundary point into the point set corresponding to the minimum distance; otherwise, a new point set for the side is created, and the current boundary point is added into the new point set. Here, the preset distance threshold is a maximum distance between two boundary points of a preset continuous distribution. And then, updating the next boundary point of the side as the current boundary point, and continuing to process according to the above mode until all the boundary points of the side are traversed to obtain a plurality of point sets corresponding to the side. In any side of the initial outer contour of the lung region, the boundary points belonging to the real contour should be continuously distributed, so that a suitable preset distance threshold can be set according to image parameters of the lung image, such as pixel spacing, to distinguish the continuously distributed boundary points. Each point set obtained by the method comprises a plurality of boundary points of the initial outer contour of the side lung area, and all the boundary points in a single point set can form a continuous curve.
On the basis, the point set with the most boundary points is selected as the fine outer contour of the side lung area, namely, the false alarm boundary points in the initial outer contour of the side lung area are filtered while the integrity of the outer contour of the side lung area is ensured as much as possible, so that the fine outer contour of the side lung area can accord with the continuity characteristic of the outer contour of the lung area. Based on the fine outer contours of the lung areas on the two sides, the edge fitting result of the lung area more fitting the real contour of the lung area can be obtained, the accuracy of the inclination angle of the lung area determined based on the edge fitting result is improved, and therefore the lung image is automatically corrected to a more standard angle. Based on any of the above embodiments, in the method, step 140 specifically includes:
step 141, performing ellipse fitting on the fine outer contours of the left side and the right side to determine the inclination angle of the lung region;
and 142, performing angle correction on the lung image based on the inclination angle.
Specifically, ellipse fitting is performed based on the fine outer contours on the left and right sides of the initial outer contour, and a center point, a long axis, a short axis and an inclination angle of the fitted ellipse are obtained. Wherein, the standard equation of the ellipse obtained by fitting can be expressed as:
wherein a and b are respectively the short axis and the long axis of the ellipse, theta is the included angle between the ellipse and the horizontal direction, and x and y are respectively the abscissa and the ordinate of the ellipse obtained by fitting.
After the included angle between the ellipse and the horizontal direction is obtained, the included angle can be used as the included angle between the lung region and the horizontal direction, namely the inclined angle of the lung region. Then, based on the inclination angle, the lung image is subjected to angle correction.
Optionally, based on the ellipse obtained by fitting, the intersection point of the major axis and the minor axis of the ellipse is used as a rotation center, and the whole lung image or the lung region in the lung image is rotated, wherein the position of each pixel point in the lung region in the whole lung image or the lung image after rotation is calculated according to the inclination angle. The angle correction is carried out on the whole lung image according to the inclination angle determined by ellipse fitting, and the lung image can be automatically corrected to a more standard angle.
According to the method provided by the embodiment of the invention, the fine outer contours of the left side and the right side are subjected to ellipse fitting to obtain the inclination angle of the lung region, and the lung image is subjected to angle correction based on the inclination angle, so that the accurate correction of the lung image angle is realized.
When the difference of standing postures of a patient who shoots a lung image is too large or the extraction effect of the outline of the lung region is not ideal, partial false alarm boundary points occur, the ellipse fitting method is usually sensitive to the false alarm boundary points, so that the inclination angle obtained based on ellipse fitting is unreasonable, and the obtained inclination angle is too large generally, so that unreasonable strong correction is caused. Therefore, when the inclination angle obtained by ellipse fitting is not reasonable, the inclination angle needs to be corrected, so that a more accurate and reasonable inclination angle is obtained.
In this regard, according to any of the above embodiments, the method further includes, after the step 141:
and if the inclination angle of the lung region is larger than the preset angle threshold, correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left lung region and the right lung region of the lung region.
Specifically, the ellipse fitting method is sensitive to false alarm boundary points, which may cause an excessively large tilt angle, so that it is determined whether the tilt angle obtained by ellipse fitting is greater than a preset angle threshold, and if so, the tilt angle is corrected. The preset angle threshold is the maximum angle of a preset reasonable inclination angle.
In correcting the inclination angle, the lung region is first divided into a left lung region and a right lung region. Alternatively, all connected regions may be acquired in a mask image of a lung region of the lung image, and the connected regions are screened, and the two connected regions with the largest area are used as the left and right lung regions.
Then, based on the positions of the top points and the bottom points of the left lung area and the right lung area of the lung area, the inclination angle of the left lung area and the inclination angle of the right lung area are obtained, then the inclination angles of the left lung area and the right lung area are comprehensively analyzed, the inclination angle of the whole lung area is recalculated, and the inclination angle of the lung area obtained by ellipse fitting is corrected according to the inclination angles so as to correct the angle of the lung image. The top points of the left and right lung areas are the points with the minimum vertical coordinate in the pixel points of the left and right lung areas, and correspondingly, the bottom points of the left and right lung areas are the points with the maximum vertical coordinate in the pixel points of the left and right lung areas; or, the vertex of the left and right lung regions is a point with the largest vertical coordinate among the pixel points of the left and right lung regions, and correspondingly, the bottom point of the left and right lung regions is a point with the smallest vertical coordinate among the pixel points of the left and right lung regions.
It should be noted that, according to actual needs, the inclination angle of the lung region may also be determined directly based on the positions of the top point and the bottom point of the left and right lung regions of the lung region, and the angle correction of the lung image is performed without performing ellipse fitting on the fine outer contours of the left and right sides.
According to the method provided by the embodiment of the invention, when the inclination angle obtained by ellipse fitting is too large, the inclination angle of the lung region is corrected based on the positions of the top point and the bottom point of the left lung region and the right lung region, the unreasonable inclination angle is corrected, and the accuracy of correcting the lung image angle is improved.
Based on any of the above embodiments, fig. 3 is a schematic flow chart of a method for correcting an inclination angle according to an embodiment of the present invention, as shown in fig. 3, in the method, correcting an inclination angle of a lung region based on positions of a vertex and a bottom point of left and right lung regions of the lung region specifically includes:
step 141-1, determining a first angle between a connecting line of a top point and a bottom point of a left lung area of the lung area and the vertical direction, a second angle between a connecting line of a top point and a bottom point of a right lung area and the vertical direction, and a third angle between a connecting line of a top point of the left lung area and a top point of the right lung area and the horizontal direction;
step 141-2, the tilt angle of the lung region is corrected based on the first, second, and third angles.
Specifically, the apex and the bottom point of the left lung region, the apex and the bottom point of the right lung region, and the apex of the left lung region and the apex of the right lung region are connected, respectively. And then, acquiring a first included angle between a connecting line of the top point and the bottom point of the left lung area and the vertical direction, a second included angle between a connecting line of the top point and the bottom point of the right lung area and the vertical direction, and a third included angle between a connecting line of the top point of the left lung area and the top point of the right lung area and the horizontal direction. The first included angle can represent the inclination angle of the left lung area, the second included angle can represent the inclination angle of the right lung area, and the third included angle can represent the inclination angle of the vertex connecting line of the left lung area and the right lung area.
Then, based on the first included angle, the second included angle and the third included angle, the inclination angle of the lung region is recalculated, and the inclination angle of the lung region obtained by ellipse fitting is corrected according to the calculated inclination angle, so that the angle correction of the lung image can be performed. Optionally, an average of the first included angle, the second included angle, and the third included angle is used as the corrected lung region inclination angle, and the specific calculation method is as follows:
θ＝(α1+α2+β1)/3
wherein, α1、α2And β1Respectively a first included angle, a second included angle and a third included angle, and theta is the corrected lung region inclination angle.
Fig. 4 is a schematic diagram of the first included angle, the second included angle, and the third included angle provided by the embodiment of the present invention, and as shown in fig. 4, a first included angle α between a line connecting the top point and the bottom point of the left lung area and the vertical direction is determined1And a second angle α between the vertical and a line connecting the apex and the base of the right lung region2And a third angle β between a line connecting the apex of the left lung region and the apex of the right lung region and the horizontal direction1. The lung image can be corrected to a comparatively standard by determining the obtained inclination angle based on the first included angle, the second included angle and the third included angleAnd (5) within the range.
Based on any of the above embodiments, fig. 5 is a schematic flowchart of a method for correcting an angle of a lung image according to another embodiment of the present invention, as shown in fig. 5, the method includes:
Fig. 6 is a schematic diagram illustrating the effect of the angle correction method according to the embodiment of the present invention, as shown in fig. 6, the ellipse frame in the diagram is obtained after ellipse fitting is performed on the fine outer contours on the left and right sides, and the lung image is rotated based on the inclination angle of the ellipse obtained by fitting, so that the lung image can be corrected to a relatively normal angle.
Based on any of the above embodiments, fig. 7 is a schematic structural diagram of an apparatus for angle correction of lung images according to an embodiment of the present invention, as shown in fig. 7, the apparatus includes a lung region determining unit 710, an initial outline extracting unit 720, a fine outline determining unit 730, and an angle correcting unit 740.
The lung region determining unit 710 is configured to determine a lung region in the lung image;
the initial outline extracting unit 720 is used for extracting an initial outline of the lung region;
the fine outer contour determining unit 730 is configured to determine a fine outer contour of the initial outer contour based on a distance between each boundary point on either of the left and right sides of the initial outer contour;
the angle correction unit 740 is configured to determine the inclination angle of the lung region based on the fine outer contours of the left and right sides, and perform angle correction on the lung image based on the inclination angle.
The device provided by the embodiment of the invention determines the fine outer contours of the left side and the right side based on the distance between each boundary point on any one of the left side and the right side of the initial outer contour of the lung region, then determines the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performs angle correction according to the inclination angle, thereby realizing automatic angle correction of lung images.
Based on any of the above embodiments, the fine outline determining unit 730 is specifically configured to:
dividing the initial outer contour into a left side and a right side;
clustering each boundary point on any side based on the distance between the boundary points on the side to obtain a plurality of point sets aiming at the side;
and determining the fine outer contour of the side based on the point set of the side containing the maximum number of boundary points.
According to the device provided by the embodiment of the invention, each boundary point on any side is clustered based on the distance between the boundary points on the side to obtain a plurality of point sets, and the fine outer contour of the side is determined based on the point set with the largest number of boundary points, so that the accuracy of contour extraction is improved.
Based on any one of the above embodiments, in the apparatus, the dividing of the initial outer contour into the left and right sides specifically includes:
and taking the boundary point with the minimum abscissa in the current row of the initial outline as a left boundary point, taking the boundary point with the maximum abscissa as a right boundary point, and updating the next row into the current row.
Based on any of the above embodiments, in the apparatus, based on a distance between each boundary point on any side, clustering each boundary point on the side to obtain a plurality of point sets for the side, specifically including:
if the minimum distance between the current boundary point on any side and each boundary point in each point set on the side is smaller than a preset distance threshold, adding the current boundary point into the point set corresponding to the minimum distance, and updating the next boundary point on the side as the current boundary point; otherwise, a new point set for the side is created, the current boundary point is added into the new point set, and the next boundary point of the side is updated to be the current boundary point.
Based on any of the above embodiments, in the apparatus, the angle correction unit 740 is specifically configured to:
carrying out ellipse fitting on the fine outer contours of the left side and the right side to determine the inclination angle of the lung region;
and carrying out angle correction on the lung image based on the inclination angle.
According to the device provided by the embodiment of the invention, the fine outer contours of the left side and the right side are subjected to ellipse fitting to obtain the inclination angle of the lung region, and the angle of the lung image is corrected based on the inclination angle, so that the accurate correction of the angle of the lung image is realized.
Based on any embodiment, in the device, performing ellipse fitting on the fine outer contours of the left and right sides to determine the inclination angle of the lung region, and then:
and if the inclination angle of the lung region is larger than the preset angle threshold, correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left lung region and the right lung region of the lung region.
According to the device provided by the embodiment of the invention, when the inclination angle obtained by ellipse fitting is too large, the inclination angle of the lung region is corrected based on the positions of the top point and the bottom point of the left lung region and the right lung region, the unreasonable inclination angle is corrected, and the accuracy of correcting the lung image angle is improved.
Based on any one of the above embodiments, in the apparatus, the correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left and right lung regions of the lung region specifically includes:
determining a first included angle between a connecting line of a top point and a bottom point of a left lung area of the lung area and the vertical direction, a second included angle between a connecting line of a top point and a bottom point of a right lung area and the vertical direction, and a third included angle between a connecting line of a top point of the left lung area and a top point of the right lung area and the horizontal direction;
and correcting the inclination angle of the lung region based on the first included angle, the second included angle and the third included angle.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 8, the electronic device may include: a processor (processor)810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call logical commands in the memory 830 to perform the following method: determining a lung region in the lung image; extracting an initial outer contour of the lung region; determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one; and determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
In addition, the logic commands in the memory 830 can be implemented in the form of software functional units and stored in a computer readable storage medium when the logic commands are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of commands for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Embodiments of the present invention further provide a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the method provided in the foregoing embodiments when executed by a processor, and the method includes: determining a lung region in the lung image; extracting an initial outer contour of the lung region; determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one; and determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes commands for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for angular correction of a lung image, comprising:
determining a lung region in the lung image;
extracting an initial outer contour of the lung region;
determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one;
and determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
2. The method for angular correction of pulmonary images according to claim 1, wherein the determining the refined outer contour of either side based on the distance between the boundary points of either side of the initial outer contour comprises:
dividing the initial outer contour into a left side and a right side;
clustering the boundary points on any side based on the distance between the boundary points on any side to obtain a plurality of point sets for any side;
determining a fine outline of the any side based on a point set of the any side with the maximum number of boundary points.
3. The method for angular correction of pulmonary images of claim 2, wherein the dividing the initial outer contour into left and right sides specifically comprises:
and taking the boundary point with the minimum abscissa in the current row of the initial outer contour as a left boundary point, taking the boundary point with the maximum abscissa as a right boundary point, and updating the next row into the current row.
4. The method of claim 2, wherein the clustering the boundary points on either side based on the distance between the boundary points on either side to obtain a plurality of point sets for either side comprises:
if the minimum distance between the current boundary point on any side and each boundary point in each point set on any side is smaller than a preset distance threshold, adding the current boundary point into the point set corresponding to the minimum distance, and updating the next boundary point on any side as the current boundary point; otherwise, a new point set for any side is created, the current boundary point is added into the new point set, and the next boundary point on any side is updated to be the current boundary point.
5. The method for angular correction of pulmonary images according to any one of claims 1 to 4, wherein the determining a tilt angle of the lung region based on the fine contour on the left and right sides and performing angular correction on the pulmonary image based on the tilt angle comprises:
carrying out ellipse fitting on the fine outer contours of the left side and the right side to determine the inclination angle of the lung region;
and performing angle correction on the lung image based on the inclination angle.
6. The method of claim 5, wherein the fitting of the ellipse to the fine outer contours of the left and right sides to determine the angle of inclination of the lung region further comprises:
and if the inclination angle of the lung region is larger than a preset angle threshold, correcting the inclination angle of the lung region based on the positions of the top point and the bottom point of the left lung region and the right lung region of the lung region.
7. The method of claim 6, wherein the correcting the angle of inclination of the lung region based on the positions of the top and bottom points of the left and right lung regions of the lung region comprises:
determining a first included angle between a connecting line of a top point and a bottom point of a left lung area of the lung area and the vertical direction, a second included angle between a connecting line of a top point and a bottom point of a right lung area and the vertical direction, and a third included angle between a connecting line of a top point of the left lung area and a top point of the right lung area and the horizontal direction;
and correcting the inclination angle of the lung region based on the first included angle, the second included angle and the third included angle.
8. An apparatus for angular correction of pulmonary images, comprising:
a lung region determining unit for determining a lung region in the lung image;
an initial outline extraction unit for extracting an initial outline of the lung region;
a fine outer contour determining unit for determining a fine outer contour of any one of the left and right sides of the initial outer contour based on a distance between each boundary point of the any one;
and the angle correction unit is used for determining the inclination angle of the lung region based on the fine outer contours of the left side and the right side, and performing angle correction on the lung image based on the inclination angle.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for angular correction of pulmonary images according to any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for angular rectification of pulmonary images according to any one of claims 1 to 7.
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